Personalized algorithm recommendation has brought new breakthroughs and challenges to reading services,and exploring the influencing factors of users'willingness to continue using personalized algorithm recommended reading service can provide reference for the optimization of related services.Based on the research framework of SOR theory,combined with TAM and ECM-ISC model,this study constructs a model of the influencing factors of users'continuous usage intention of personalized algorithmic recommendation reading service,and carries outempirical analysis through questionnaire survey method.The research finds that the functions and features of personalized algorithmic reading services can significantly affect users'intrinsic perceptions and their willingness to continue using them.Perceived usefulness,perceived ease of use,and satisfaction positively affect users'intention to continue using personalized algorithmic reading services.Perceived privacy risk affects satisfaction,which in turn affects intention to continue using the service.The industry should strive to improve the accuracy and diversity of recommended readings,improve the interface design of the recommendation system,flexibly adjust the number of recommended readings,and upgrade privacy policy service.
personalized algorithm recommendation servicerecommended reading serviceusercontinuous use intention
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